SOTAVerified

3D Object Detection

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Papers

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Showing 926–950 of 1576 papers

TitleStatusHype
GraVoS: Voxel Selection for 3D Point-Cloud DetectionCode0
Ret3D: Rethinking Object Relations for Efficient 3D Object Detection in Driving Scenes—0
An Empirical Study of Pseudo-Labeling for Image-based 3D Object Detection—0
Aerial Monocular 3D Object DetectionCode0
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local GraphCode1
Global Hierarchical Attention for 3D Point Cloud Analysis—0
TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection—0
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions—0
PolarMix: A General Data Augmentation Technique for LiDAR Point CloudsCode2
Semi-supervised 3D Object Detection with Proficient TeachersCode1
Monocular 3D Object Detection with Depth from MotionCode2
ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object DetectionCode1
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds—0
Label-Guided Auxiliary Training Improves 3D Object DetectorCode0
Computer Vision Aided mmWave Beam Alignment in V2X CommunicationsCode0
Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise BinarizationCode1
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object DetectionCode1
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object DetectionCode2
AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object DetectionCode1
Omni3D: A Large Benchmark and Model for 3D Object Detection in the WildCode2
Boosting 3D Object Detection via Object-Focused Image FusionCode1
Densely Constrained Depth Estimator for Monocular 3D Object DetectionCode1
Multimodal Transformer for Automatic 3D Annotation and Object DetectionCode1
A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations—0
On the Robustness of 3D Object Detectors—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified